SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERFACES

Authors

  • Ms. Asmita D Rathod, Department of Computer Engineering,SRTM University, Hingoli, India.

Keywords:

two-stage crawler,, feature selection, adaptive learning., ranking

Abstract

Deep web growingat a very fast pace, lot of speculations in techniques this techniques has been added thathelpefficientlylocate deep-web interfaces. However, due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. In this paper author has proposed a two-stage framework, namely Smart Crawler, for efficient harvesting deep web interfaces. Smart Crawler performs site-based searching for center pages by usingsearch engines, avoiding visiting a large number of pages. To achieve more accurate results for a focused crawl, Smart Crawler techniques prioritize websites to highly relevant ones for a given topic. Smart Crawler achieves fast in-site searching by findingmost relevant links with an adaptive link-ranking. To eliminate bias on visiting some relevant links in hidden web directories, author has designeda link tree data structure to achieve wider coverage for a website.

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Published

2021-03-27

Issue

Vol. 3 No. 4 (2016): IJIERT

Section

Articles

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How to Cite

Ms. Asmita D Rathod,. (2021). SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERFACES. International Journal of Innovations in Engineering Research and Technology, 3(4), 1-9. https://repo.ijiert.org/index.php/ijiert/article/view/871